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<title>collectl - The Math</title>
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<center><h1>The Math</h1></center>
<p>
<h3>The Basics</h3>
At first glance, the way collectl calculates its numbers is pretty straight forward.  It
looks at successive intervals of counters, calculates their differences and divides by
the interval, the result of which is the counter's rate.  If -on is specified collectl
does not divide by the interval and simply reports the difference.
However, one occasionally may see numbers that don't make sense, such as a 1Gb network
reporting rates almost <a href=NetworkStats.html>double</a> what it is capable of or 
other anomolous numbers.  
<p>
<h3>The Interval Time Stamps</h3>
By design, collectl takes one time stamp at the start of each monitoring interval and
associates that time with all the samples taken during that interval.
This has been done for one major reason - there needs to be a single time 
associated with all data points, especially if you want to plot the data.
The overhead in collecting the data is fairly constant and therefore the interval for 
that sample is fairly consistent and so the rates reported are also consistent.
<p>
However, there can be a problem that is important to understand and has been seen in
the past.  A device had the wrong firmware
level and under some conditions caused a long delay in the middle of the collection 
interval.  Some samples were collected close the the starting time of that
interval while all that followed the delay were actually collected at a time much later
than was being reported.
<p>
Consider the following in which we're looking at raw data collected for 2 subsystems,
call them XXX and YYY.  Let's also assume that the counters we're monitoring are
increasing at a steady rate of 100 units/sec.  In this example, during the 10:00:01 interval
there was a 10 second hang in collecting the YYY sample.  The XXX sample was correctly
recorded, but by the time the YYY sample was collected, 1000 units were recorded.  As we
move to the next interval which was delayed by 10 seconds, the sample for XXX has
accumulated 1000 units and the sample for YYY is 100.

<pre>
TYPE            XXX     YYY
10:00:00        100     100
10:00:01        200     1100
10:00:11        1200    1200
10:00:12        1300    1300
</pre>

The problem here is when reporting the 2 rates at 10:00:01, we'll see a rate of 1000
units/sec for YYY because based on the timestamp that interval only appears to be 1
second long.  Conversely, the rate reported for that same subsystem at 10:00:11 will be
10 units/sec because this interval is reported as 10 seconds long.  Also note that for
this interval the counter for XXX has been incremented correctly and the resultant rates
are reported correctly.
This is because the sampling occured before the delays.  If
one were to move the timestamp to the end of the interval, it would fix the problem with
YYY, but then move it to XXX.
<p>
It IS important to understand that this is only a problem if the delay is during the data
collection itself.  If there is a system delay that causes all data collection to be
delayed but once started runs as expected, <i>and this has been seen to be the typical
case</i>, the intervals may be longer but the counters will
have increased proportionaly and the results consistent.
<p>
The only real answer to this problem would be to timestamp individual samples, however
it is also felt that this problem is rare enough as to not be of serious concern and
changing the methodology of timestamping would cause more problems than it solves.
<p>
<h3>The Counter Update Rate</h3>
This is a problem that is very real and worth understanding even it if you never 
personally see it.  If the rate at which a counter is updated is too coarse, 
especially if it is close to the monitoring interval, the reported numbers will
be off.  For most of the data collectl reports on, this is not a problem because these
counters ARE updated frequently.  However, it turns out that the network data is only 
updated about once a second and in early versions of the 2.6 kernel (and may the one
you're currently running on), you may see some very strange anomolies in the output if
you look at 1-second data samples.
See <a href=NetworkStats.html>this page<a> for more details.
<p>
<h3>In conclusion</h3>
As they say, <a href=http://en.wikipedia.org/wiki/Garbage_in,_garbage_out>
<i>garbage in, garbage out</i></a> and so if the number you're seeing look wrong, it's
worth trying to understand why and you shouldn't necessary take them as face
value.
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